neuralgcm/neuralgcm

Health v2 · maintenance only

Adoption not part of the score

1008 stars · 133 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

NeuralGCM is a Python library for building hybrid machine-learning/physics models of the Earth's atmosphere for weather and climate simulation. It combines learned neural components with traditional general circulation model dynamics.

Use cases

• simulate weather with a hybrid ML physics model
• run atmospheric climate simulations in Python
• forecast weather using neural general circulation models
• research machine learning for weather and climate modeling
• build hybrid atmospheric models combining ML and physics

When to choose

• you need state-of-the-art hybrid ML/physics atmospheric simulation
• you are doing research on ML-based weather or climate modeling
• you want a Python library with pretrained model weights for atmospheric simulation

When to avoid

• you need a simple point-and-click weather forecast app
• you lack the computational resources (GPUs/TPUs) for atmospheric simulation
• you need operational meteorology tooling outside Python

Facets

library · maturity active

machine-learning simulation data-science machine-learning data-science python weather climate-modeling atmospheric-science hybrid-ml-physics numerical-weather-prediction jax algorithms linux macos

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markdown · JSON · MCP: product_card(name="neuralgcm/neuralgcm")